Trends in total sunshine hours, 1972–2016

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Creative Commons Attribution 4.0 International

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2069
11
Added
13 Oct 2017

This dataset was first added to MfE Data Service on 13 Oct 2017.

Trends in total sunshine hours, 1972–2016.
Sunshine is essential for our mental and physical well–being and plant growth. It is also important for tourism and recreation.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89444
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in peak UV index value, 1981–2017

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

2071
5
Added
14 Oct 2017

This dataset was first added to MfE Data Service on 14 Oct 2017.

Trends in daily peak UV index values at Invercargill, Lauder (Otago region), Christchurch, Paraparaumu (Wellington region), and Leigh (Auckland region). The strength of UV light is expressed as a solar UV index, starting from 0 (no UV) to 11+ (extreme).
Exposure to the sun's ultraviolet (UV) light helps our bodies make vitamin D, which we need for healthy bones and muscles. However, too much exposure to UV light can cause skin cancer. New Zealand has naturally high UV levels, and monitoring UV levels helps us understand the occurrence of skin cancer.
Ozone in the upper atmosphere absorbs some of the sun’s UV light, protecting us from harmful levels. The amount of UV radiation reaching the ground varies in relation to changes in the atmospheric ozone concentrations. The Antarctic ozone hole lies well to the south of New Zealand and does not have a large effect on New Zealand’s ozone concentrations.
The trend was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89469
Data type Table
Row count 5
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Oceanic sea surface temperature trends, 1993–2016

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Creative Commons Attribution 4.0 International

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2072
4
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

We used NIWA’s sea-surface temperature archive, which is derived from the Advanced Very High Resolution Radiometer (AVHRR) satellite data it receives from the US National Oceanic and Atmospheric Administration. The archive provides high spatial (approximately 1km) and high temporal (approximately six-hourly in cloud-free locations) resolution estimates of sea-surface temperatures over the New Zealand region, dating from January 1993. Uddstrom & Oien (1999) and Uddstrom (2003) describe the methods used to derive and validate the data.
Our data extends from about 30°S to 55°S, and from 160°E to 170°W and is grouped into five areas: the exclusive economic zone (EEZ), the Chatham Rise, northern subtropical waters, subantarctic waters, and the Tasman Sea.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89407
Data type Table
Row count 4
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Spring rainfall trends, 1960–2016

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Creative Commons Attribution 4.0 International

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2063
7
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

Spring rainfall trends for 30 representative sites from 1960–2016.
Rain is vital for life – it supplies the water we need to drink and to grow our food, keeps our ecosystems healthy, and supplies our electricity. New Zealand’s mountainous terrain and location in the roaring forties mean rainfall varies across the country. Changes in rainfall amount or timing can significantly affect agriculture, energy, recreation, and the environment. For example, an increase or decrease of rainfall in spring can have marked effects on crops or fish populations.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89403
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Influenza like illness weekly consultation rates, 2000–16

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Creative Commons Attribution 4.0 International

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2058
5
Added
14 Oct 2017

This dataset was first added to MfE Data Service on 14 Oct 2017.

Influenza is a potentially life-threatening virus that spreads quickly from person to person. It is a significant public health issue in this country, with 10–20 percent of New Zealanders infected every year. While influenza can occur all year round, incidence generally peaks in winter and spring in New Zealand. Some studies suggest this is because the virus can survive longer outside the body in periods of colder weather and low humidity (dry conditions).
Influenza infections may decline as our climate changes. Warmer projected temperatures and higher humidity during winter and spring may contribute to reduced annual influenza rates. However, influenza infection is also affected by factors besides temperature and humidity.
These data are reported in an annual surveillance report by the Institute of Environmental Science and Research. See the 2015 report for more information (Institute of Environmental Science and Research, 2016).
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89456
Data type Table
Row count 374
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Frost and warm days trend assessment, 1972–2016

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Creative Commons Attribution 4.0 International

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2050
13
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

The number of frost and warm days changes from year to year in response to climate variation, such as the warming pattern induced by El Niño. Climate models project we may experience fewer cold and more warm extremes in the future. Changes in the number of frost and warm days can affect agriculture, recreation, and our behaviour, for example, what we do to keep safe on icy roads or whether to use air conditioning to keep cool.
A frost day is when the minimum temperature recorded is below 0 degrees Celsius. It refers to a temperature measured in an instrument screen 1.2m above the ground rather than a ‘ground frost’. We define a warm day as having a maximum recorded temperature above 25 degrees Celsius. The threshold of 25 degrees Celsius is chosen to represent days where action might be taken to keep cool (eg turn air conditioning on).
This dataset gives the trend in frost and warm days for New Zealand, the North and South Islands, and for all 30 sites.
For frost days we have used calendar years. For warm days we have used growing season (July 1 – June 30 of the following year).
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
More information on this dataset and how it relates to our Environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89388
Data type Table
Row count 60
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in maximum highest annual wind gust, 1972–2016

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

2052
6
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

Trends in maximum highest annual wind gust, 1972–2016. The number of days with a maximum gust in the 99th percentile provides information on the frequency of extreme wind events. Percentiles are obtained from all available daily maximum wind gust data. On average, the 99th percentile daily maximum wind gust will be exceeded on approximately 3.6 days per year. Therefore, annual counts higher than this indicate more days than usual with very strong wind gusts recorded; annual counts lower than 3.6 indicate fewer strong wind gust days than usual. By using a percentile threshold we can identify events that are extreme for a particular location. Some places are naturally subject to stronger winds than others, so vegetation can become ‘wind-hardened’ and may have a higher tolerance to high wind gusts (eg a 100 km/hr wind gust may be damaging at one location, but not at another). Using a relative threshold accounts for these differences and better captures extreme wind gust occurrences. The highest maximum gust per year and the average annual highest maximum wind gust both provide information on the magnitude of extreme wind events.
Steady wind can be an important resource, but strong gusts can damage property, topple trees, and disrupt transportation, communications, and electricity. Extreme wind events can occur with frontal weather systems, around strong convective storms such as thunderstorms, and with ex–tropical cyclones. Projections indicate climate change may alter the occurrence of extreme wind events, with the strength of extreme winds expected to increase over the southern half of the North Island and the South Island, especially east of the Southern Alps, and decrease from Northland to Bay of Plenty. Monitoring can help us gauge the potential of, and prepare for, such events.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89424
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

The annual SOI compared with New Zealand's detrended temperature series (1909–2013)

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Creative Commons Attribution 3.0 New Zealand

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2041
19
Added
01 Oct 2015

This dataset was first added to MfE Data Service on 01 Oct 2015.

El Niño Southern Oscillation (ENSO). It is an important predictor of how tropical oceans and climate might influence New Zealand’s climate. Being able to predict the timing and intensity of an El Niño or La Niña climate phase is important in predicting and preparing for extreme climatic conditions, such as strong winds, heavy rain, or drought. Such extreme conditions can impact on our environment, industries, and recreational activities. ENSO is commonly measured using the Southern Oscillation Index (SOI).
In New Zealand, an El Niño phase can cause colder winters. In summer it can result in more rain in the west and drought in the east. A La Niña phase can cause warmer temperatures, more rain in the north-east, and less rain in the south and south-west.
This dataset relates to the "El Niño Southern Oscillation" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52590
Data type Table
Row count 105
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Melanoma registration trends, 1996–2013

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Creative Commons Attribution 4.0 International

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2045
4
Added
14 Oct 2017

This dataset was first added to MfE Data Service on 14 Oct 2017.

New Zealand and Australia have the world’s highest rates of melanoma, the most serious type of skin cancer. Melanoma is mainly caused by exposure to ultraviolet (UV) light, usually from the sun. New Zealand has naturally high UV levels, especially during summer.
The risk of developing melanoma is affected by factors such as skin colour and type, family history, and the amount of sun exposure. Melanoma can affect people at any age, but the chance of developing a melanoma increases with age. We report on age-standardised rates of melanoma to account for the increasing proportion of older people in our population.
Our data on melanoma registrations come from the New Zealand Cancer Registry and the Ministry of Health's Mortality Collection. The passing of the Cancer Registry Act 1993 and Cancer Registry Regulations 1994 led to significant improvements in data quality and coverage (Ministry of Health, 2013). A sharp increase in registrations after 1993 is likely to have been related to these legislative and regulatory changes; for this reason we have only analysed data from 1996.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89460
Data type Table
Row count 57
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in percent of annual rainfall in the 95th percentile (r95ptot), 1960–2016

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Creative Commons Attribution 4.0 International

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2033
5
Added
13 Oct 2017

This dataset was first added to MfE Data Service on 13 Oct 2017.

Trends in percent of annual rainfall in the 95th percentile (r95ptot), 1960–2016.
Intense rainfall can result in flash floods or land slips that damage homes and property, disrupt transportation, and endanger lives. It can also interfere with recreation and increase erosion. Changes to the frequency of intense rainfall events can alter biodiversity.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89434
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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